Pkgndep: a tool for analyzing dependency heaviness of R packages.
Journal
Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944
Informations de publication
Date de publication:
02 09 2022
02 09 2022
Historique:
received:
29
03
2022
revised:
24
06
2022
accepted:
07
07
2022
pubmed:
9
7
2022
medline:
15
11
2022
entrez:
8
7
2022
Statut:
ppublish
Résumé
Numerous R packages have been developed for bioinformatics analysis in the last decade and dependencies among packages have become critical issues to consider. In this work, we proposed a new metric named dependency heaviness that measures the number of dependencies that a parent uniquely brings to a package and we proposed possible solutions for reducing the complexity of dependencies by optimizing the use of heavy parents. We implemented the metric in a new R package pkgndep which provides an intuitive way for dependency heaviness analysis. Based on pkgndep, we additionally performed a global analysis of dependency heaviness on CRAN and Bioconductor ecosystems and we revealed top packages that have significant contributions of high dependency heaviness to their child packages. The package pkgndep and documentations are freely available from the Comprehensive R Archive Network https://cran.r-project.org/package=pkgndep. The dependency heaviness analysis for all 22 076 CRAN and Bioconductor packages retrieved on June 8, 2022 are available at https://pkgndep.github.io/. Supplementary data are available at Bioinformatics online.
Identifiants
pubmed: 35801905
pii: 6633919
doi: 10.1093/bioinformatics/btac449
pmc: PMC9438947
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4248-4251Subventions
Organisme : National Center for Tumor Diseases
Organisme : Molecular Precision Oncology Program
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press.